We present a framework that enables a belief-desire-intention (BDI) agent to dynamically choose its intention reconsideration policy in order to perform optimally in accordance with the current state of the environment. Our framework integrates an abstract BDI agent architecture with the decision theoretic model for discrete deliberation scheduling of Russell and Wefald. As intention reconsideration determines an agent’s commitment to its plans, this work increases the level of autonomy in agents, as it pushes the choice of commitment level from design-time to run-time. This makes it possible for an agent to operate effectively in dynamic and open environments, whose behaviour is not known at design time. Following a precise formal definition of the framework, we present an empirical analysis that evaluates the run-time policy in comparison with design-time policies. We show that an agent utilising our framework outperforms agents with fixed policies.